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Development and Validation of the Pediatric Risk Estimate Score for Children Using Extracorporeal Respiratory Support (Ped-RESCUERS) Ryan P

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Development and Validation of the Pediatric Risk Estimate Score for Children Using Extracorporeal Respiratory Support (Ped-RESCUERS) Ryan P Development and validation of the pediatric risk estimate score for children using extracorporeal respiratory support (Ped-RESCUERS) Ryan P. Barbaro, University of Michigan Philip S. Boonstra, University of Michigan Matthew Paden, Emory University Lloyd A. Roberts, Monash University Melbourne Gail M. Annich, University of Toronto Robert H. Bartlett, University of Michigan Frank W. Moler, University of Michigan Matthew M. Davis, University of Michigan Journal Title: Intensive Care Medicine Volume: Volume 42, Number 5 Publisher: Springer (part of Springer Nature): Springer Open Choice Hybrid Journals - CC-BY-NC | 2016-05-01, Pages 879-888 Type of Work: Article | Post-print: After Peer Review Publisher DOI: 10.1007/s00134-016-4285-8 Permanent URL: https://pid.emory.edu/ark:/25593/tnns8 Final published version: http://dx.doi.org/10.1007/s00134-016-4285-8 Copyright information: © 2016, Springer-Verlag Berlin Heidelberg and ESICM. Accessed September 25, 2021 1:40 AM EDT HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Intensive Manuscript Author Care Med. Author Manuscript Author manuscript; available in PMC 2019 February 18. Published in final edited form as: Intensive Care Med. 2016 May ; 42(5): 879–888. doi:10.1007/s00134-016-4285-8. Development and Validation of the Pediatric Risk Estimate Score for Children Using Extracorporeal Respiratory Support (Ped- RESCUERS) Ryan P. Barbaro, MD, MSc1,2, Philip S. Boonstra, PhD3, Matthew L. Paden, MD4, Lloyd A. Roberts, MBBS5, Gail M. Annich, MD, MS6, Robert H. Bartlett, MD7, Frank W. Moler, MD, MS2, and Matthew M. Davis, MD, MAPP1,2,8,9 1Department of Pediatrics, University of Michigan, Ann Arbor; 2Child Health Evaluation and Research (CHEAR) Unit, University of Michigan, Ann Arbor; 3School of Public Health Department of Biostatistics, University of Michigan, Ann Arbor 4Division of Pediatric Critical Care, Emory University, Atlanta, Georgia; 5Intensive Care Department, Alfred Hospital and School of Public Health and Preventative Medicine, Monash University Melbourne, Australia; 6Critical Care Medicine, University of Toronto, Toronto, Canada; 7Department of Surgery, University of Michigan, Ann Arbor; 8Department of Internal Medicine, University of Michigan, Ann Arbor, 9Gerald R. Ford School of Public Policy and Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor Abstract Purpose: To develop and validate the Pediatric Risk Estimation Score for Children Using Extracorporeal Respiratory Support (Ped-RESCUERS). Ped-RESCUERS is designed to estimate the in-hospital mortality risk for children prior to receiving respiratory extracorporeal membrane oxygenation (ECMO) support. Methods: This study used data from an international registry of patients aged 29 days to less than 18 years who received ECMO support from 2009 to 2014. We divided the registry into development and validation datasets by calendar date. Candidate variables were selected for model inclusion if the variable independently changed the mortality risk by at least 2 % in a Bayesian logistic regression model with in-hospital mortality as the outcome. We characterized the model’s ability to discriminate mortality with the area under curve (AUC) of the receiver operating characteristic. Address correspondence to: Ryan Barbaro, University of Michigan, 1500 East Medical Center Drive, Mott F-6790/Box 5243, Ann Arbor, MI 48109, [email protected], (734) 764-5302. Reprints: Reprints will not be ordered. Conflict of Interest: Drs. Bartlett, Paden, and Annich acknowledge that they are on the Extracorporeal Life Support Organization steering committee. The other authors have no conflicts of interest relevant to this article to disclose. Barbaro et al. Page 2 Results: From 2009 to 2014, 2458 non-neonatal children received ECMO for respiratory Author ManuscriptAuthor Manuscript Author Manuscript Author Manuscript Author support, with a mortality rate of 39.8 %. The development dataset contained 1611 children receiving ECMO support from 2009 to 2012. The model included the following variables: pre- ECMO pH, pre-ECMO arterial partial pressure of carbon dioxide, hours of intubation prior to ECMO support, hours of admission at ECMO center prior to ECMO support, ventilator type, mean airway pressure, pre-ECMO use of milrinone, and a diagnosis of pertussis, asthma, bronchiolitis, or malignancy. The validation dataset included 438 children receiving ECMO support from 2013 to 2014. The Ped-RESCUERS model from the development dataset had an AUC of 0.690, and the validation dataset had an AUC of 0.634. Conclusions: Ped-RESCUERS provides a novel measure of pre-ECMO mortality risk. Future studies should seek external validation and improved discrimination of this mortality prediction tool. Keywords extracorporeal membrane oxygenation; risk assessment; risk adjustment; severity of illness index; mortality; pediatric Introduction The case-mix adjusted mortality rate is considered essential for accurate evaluation of hospital-level outcomes [1–7]. Numerous clinical registries have incorporated risk-adjusted mortality measurements to enhance internal and external benchmarking and as drivers for quality improvement among participating institutions [8–12]. Researchers have applied risk- adjustment tools to facilitate observational research [2,1,13], and physicians can utilize risk- adjustment tools to anticipate the mortality risk for patients [14,15]. In pediatric extracorporeal membrane oxygenation (ECMO) for respiratory support such a risk- adjustment tool would be of great utility in clinical and analytic applications. owever, no such risk-adjustment tool exists [16]. In this study we use data from the Extracorporeal Life Support Organization (ELSO) registry, an international registry of 298 centers, to develop and internally validate the Pediatric Risk Estimate Score for Children Using Extracorporeal Respiratory Support (Ped- RESCUERS) tool. Ped-RESCUERS is designed to estimate the pre-ECMO risk of in- hospital death for children receiving respiratory ECMO support. Materials and Methods This study was designed in accordance with the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement [17]. As a retrospective analysis of deidentified data, formal consent was not required, and it was determined to be exempt from human subjects review by the Institutional Review Board of the University of Michigan Medical School. Intensive Care Med. Author manuscript; available in PMC 2019 February 18. Barbaro et al. Page 3 Patient Selection Author ManuscriptAuthor Manuscript Author Manuscript Author Manuscript Author We queried the ELSO registry for all pediatric patients aged 29 days to <18 years who received ECMO support for respiratory failure from 2009–2014. A priori, we chose 2009 as the start date for data accrual because advances in ECMO technology from that year onward have been reported to enhance delivery of ECMO support [18,19]. If a patient was placed on ECMO more than once, we only considered the first ECMO run. The development dataset incorporated data among children who received pediatric respiratory ECMO between January 1, 2009, and December 31, 2012. A validation dataset was created from children who received respiratory ECMO support between January 1, 2013 and December 31, 2014. We limited our validation dataset to those with complete data for selected variables (Figure 1). Multiple Imputations We derived Ped-RESCUERS from a Bayesian logistic regression model predicting mortality. Our development dataset included variables with missing data (Online Resource 1-Table e1). We addressed missing data through multiple imputation with iterative chained equations [20–22] because logistic regression models that limit analysis to patients with complete data can lead to biased results [17,23]. Multiple imputation uses the partial information available in the observation and data contained in other observations in the dataset to predict an observation’s missing data (additional details in Online Resource 1-Supplemental Methods) [20]. Importantly, the outcome variable of death prior to hospital discharge contained no missing observations. Candidate Variables We adapted primary diagnostic fields from a previous publication of pediatric respiratory ECMO mortality risk factors [24] (Table 1) and defined diagnostic groups using International Classification of Disease-9-Clinical Modification (ICD-9-CM) diagnostic codes. Primary diagnoses were not considered as one variable with 15 categories, but rather as 15 present or absent dummy variables. This allowed the contribution of each diagnosis to the model to be considered individually. We recoded all other categorical variables into dummy variables. This yielded 53 candidate variables, listed in Table 1 and Table 2. In addition to primary diagnoses, candidate variables included clinical data collected ≤ 6 hours prior to ECMO, such as physiologic (the worst pre-ECMO blood gas and lowest systolic blood pressure) and therapeutic (ventilator settings and number of days of mechanical ventilation prior to ECMO) data. Other variables included the presence of pre-ECMO cardiac arrest, pre-ECMO renal failure and any clinical comorbidities as defined by Feudtner et al. [25] (additional details in Online Resource 1- Supplemental Methods and Table e2). A priori we identified two types of interactions to consider: the interaction between ventilator settings and ventilator type and an interaction
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